Bruce Tidor

Biosketch

A.B. Chemistry & Physics, Harvard, 1983
M.Sc. Biochemistry, Oxford, 1985
Ph.D. Biophysics, Harvard, 1990
Whitehead Fellow, Whitehead Institute for Biomedical Research, 1990
Assistant Prof., Dept. of Chemistry, MIT, 1994
Associate Prof., Dept. of Chemistry, MIT, 1999
Associate Professor, Biological Engineering Division & Department of Electrical Engineering and Computer Science, MIT, 2001
Member, MIT Computer Science and Artificial Intelligence Laboratory, 2002
Professor, Biological Engineering Division and Department of Electrical Engineering and Computer Science, 2005

Research Focus

Research in the Tidor Group is focused on the analysis of complex biological systems at the molecular and network levels. Projects at the molecular level study the structure and properties of proteins, nucleic acids, and their complexes. Investigations probe the sources of stability and specificity that drive macromolecular folding, binding, and catalysis. Studies are aimed at dissecting the interactions responsible for the specific structure of folded proteins and the binding geometry of molecular complexes. The roles played by salt bridges, hydrogen bonds, side-chain packing, rotameric states, solvation, and the hydrophobic effect in native biomolecules are being explored, and strategies for re-casting these roles through structure-based molecular design are being developed. Work at the network level involves the study of biochemical regulatory networks and signal transduction pathways in cells. The development of approaches to relate network topology to functional characteristics is fundamental to this research. Significant effort is being applied to extracting the design principles for biological networks and to understanding the control functions implemented. The insights resulting from this work will provide a strong foundation for understanding biological systems; moreover, they will be useful for the development of therapies that ameliorate disease states, as well as for the construction of new synthetic systems from biological components. The methods of theoretical and computational biophysics and approaches from computer science, artificial intelligence, applied mathematics, and chemical and electrical engineering play fundamental roles in this work.